Prediction of Distal Residue Participation in Enzyme Catalysis

Article Protein Science DOI 10.1002/pro.2648

Heather R. Brodkina,b,1

Nicholas A. DeLateura,2

Srinivas Somarowthua,3

Caitlyn L. Millsa

Walter R. Novakb,4

Penny J. Beuninga

Dagmar Ringeb

Mary Jo Ondrechena*

aDepartment of Chemistry and Chemical Biology, Northeastern University, Boston, MA, 02115, USA, and bDepartments of Biochemistry and Chemistry, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA 024549110, USA1Present address: Alkermes, Inc., 852 Winter Street, Waltham, MA 02451, USA 2Present address: Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139 3Present address: Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520 4Present address: Department of Chemistry, Wabash College, Crawfordsville, IN 47933

*To whom correspondence should be sent. Corresponding author information: Professor Mary Jo Ondrechen Department of Chemistry and Chemical Biology Northeastern University 360 Huntington Avenue Boston, MA 02115 USA Telephone: +16173732856 Fax: +16173738795 Email: [email protected]

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/pro.2648 © 2014 The Protein Society Received: Nov 22, 2014; Revised: Jan 10, 2015; Accepted: Jan 26, 2015 This article is protected by copyright. All rights reserved. Protein Science Page 2 of 42

Abstract

A scoring method for the prediction of catalytically important residues in enzyme structures is presented and used to examine the participation of distal residues in enzyme catalysis. Scores are based on the Partial Order Optimum Likelihood (POOL) machine learning method, using computed electrostatic properties, surface geometric features, and information obtained from the phylogenetic tree as input features.

Predictions of distal residue participation in catalysis are compared with experimental kinetics data from the literature on variants of the featured enzymes; some additional kinetics measurements are reported for variants of Pseudomonas putida nitrile hydratase (ppNH) and for E. coli alkaline phosphatase (AP). The multilayer active sites of Pseudomonas putida nitrile hydratase and of human phosphoglucose isomerase are predicted by the POOL logZP scores, as is the singlelayer active site of Pseudomonas putida ketosteroid isomerase. The logZP score cutoff utilized here results in over prediction of distal residue involvement in E. coli alkaline phosphatase. While fewer experimental data points are available for Pseudomonas putida mandelate racemase and for human carbonic anhydrase II, the POOL logZP scores properly predict the previously reported participation of distal residues.

Keywords Remote residues; catalytic efficiency; Partial Order Optimum Likelihood; nitrile hydratase; phosphoglucose isomerase; ketosteroid isomerase; alkaline phosphatase

Abbreviations CSA – Catalytic Site Atlas INTREPID Information Theoretic Tree Traversal for Protein Functional Site Identification KSI – Ketosteroid isomerase PGI – Phosphoglucose isomerase POOL – Partial Order Optimum Likelihood THEMATICS – Theoretical Microscopic Anomalous Titration Curve Shapes

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Introduction

Many chemical reactions that require high temperature and/or extreme pH in the

laboratory are catalyzed by enzymes at physiological temperature and neutral pH. One

of the central challenges in biochemistry is to understand how enzymes achieve this

catalytic power under mild conditions. Structural and biochemical studies have now

characterized the active sites of hundreds of enzymes; nearly all of these studies have

focused on the amino acid residues in direct contact with the reacting substrate

molecule(s). A typical enzyme might consist of hundreds of residues, but only a handful

of them have been identified in the literature as catalytically important. In the manually

curated portion of the Catalytic Site Atlas (CSA),1 a database of enzyme active site

composition compiled from the experimental literature, an average of only 1.2% of the

residues in the biological units of these 170 enzymes is listed as catalytically important.

Virtually all of these reported catalytic residues are, in the active conformation of the

enzyme, in direct contact with the reacting substrate molecule(s). A recent review

surveys examples from the literature of proteins where distal residues have been shown

to participate directly in the biochemical function.2 The present paper presents a model,

based on computed chemical properties, that successfully predicts both firstshell and

more distant residues that are important for function. Model predictions are compared

with available experimental data and, for a few cases, new experimental results are

presented. The ability to predict, with a simple calculation, the involvement of distal

residues in catalytic and other processes is a very important capability for protein

engineering and for understanding how nature builds catalytic sites.

Here new computational and experimental results, together with experimental

data from the literature, are presented to show that residues that are not in direct contact

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with the reacting substrate molecule often play significant roles in catalysis, but more importantly, that their participation in catalysis is predictable with a simple calculation.

Previously we have shown3,4 that all of the residues in a protein structure may be assigned scores based on computed chemical properties and that these scores may be used to rankorder all of the residues according to their probability of functional importance. In the present work, these scores are transformed so that they are more comparable across proteins of different sizes. We now show that the pattern of these scores predicts whether an enzyme has a highly localized, compact active site, or a spatially extended, multilayer active site with extensive involvement of distal residues in catalysis and ligand binding.

For purposes of the present study, residues interacting directly with the substrate molecule are referred to as firstshell residues; other residues interacting directly with one or more firstshell residues are called secondshell residues; and finally, other residues interacting with one or more secondshell residues are called thirdshell residues. All residues defined as first, second or thirdshell thus may be thought of as members of respective spheres surrounding the reacting substrate molecule. In the present work, enzymes with available experimental data on the participation of distal residues in catalysis are the focus.

THEMATICS (THEoretical Microscopic Anomalous TItration Curve Shapes) is a computational method for the prediction of catalytic and binding residues in proteins solely from the 3D structure of the query protein.57 THEMATICS takes advantage of the unique chemical and electrostatic properties of catalytic and binding residues. In particular, the ionizable residues in active sites tend to have anomalously shaped theoretical titration curves. We have established metrics6 to quantify the degree of deviation from normal titration behavior and have shown how these metrics may be used

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to predict, with high sensitivity and specificity,7 the active site residues in a protein 3D

structure, just from a simple set of calculations.

POOL (Partial Order Optimum Likelihood)3,4,8 is a machine learning method for

the prediction of functionally important residues in protein structures. POOL, a

multidimensional, monotonicityconstrained maximum likelihood technique, utilizes input

for which the output variable (in this case the probability of functional importance of a

residue) is a monotonic function of each of the input features. POOL starts with the

hypothesis that the larger the THEMATICS metrics for a given residue, the higher the

probability that that residue is important for the biochemical function. Electrostatics

features from THEMATICS are combined with multidimensional isotonic regression to

form maximum likelihood estimates of probabilities that specific residues are active in

biochemical function. All residues are then rankordered according to their probability of

functional importance. Through the introduction of environment variables in POOL,

THEMATICS metrics are used to characterize the chemical environments of all residues,

not just the ionizable ones. Furthermore, the input to POOL is flexible, in that any

property upon which the probability of the functional importance of a residue depends

monotonically can be a POOL input feature. These include features based solely on the

structure of the query protein, such as THEMATICS metrics6,7,9 and surface geometric

properties,10 but may also include other features if they are available, such as

phylogenetic treebased scores.11 It has been demonstrated3 that POOL with purely

structurebased features performs very nearly as well as the best methods that utilize

both sequence alignments and structure. POOL with input features that include

THEMATICS, geometric data, and phylogenetic scores has been shown4 to be an even

higherperforming functional residue predictor; with these three input features,

THEMATICS is the largest contributor to the POOL predictions. In this work,

THEMATICS, the structureonly version of ConCavity,10 and INTREPID,11 are used as

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input to POOL to predict specific residues, including those outside the first shell, that are

involved in catalysis; POOL scores are used to predict the degree of spatial extension of

enzyme active sites and experimental evidence to support these predictions is

presented.

Numerous examples of distal residue involvement in enzyme specificity have

been reported in the directed evolution literature.12 For instance the activity of human carbonic anhydrase II on the ester substrate 2naphthyl acetate was increased 40fold with a triple mutant obtained through three rounds of mutagenesis, selection and recombination. Notably, all three residues were located outside of the first shell.13 In the

directed evolution of E. coli Dsialic acid aldolase to L3deoxymanno2octulosonic acid aldolase, changes in eight amino acids, all of which are located outside the first shell, were necessary to produce a mutant enzyme with a 1000fold increase in specificity for the unnatural sugar substrate, L D3deoxymanno2octulosonic acid.14 Directed

evolution techniques were also used to alter the specificity of aspartate

aminotransferase.15 An enzyme variant containing 17 amino acid substitutions resulted in a 106fold increase in catalytic rate for the nonnative valine substrate.15 Interestingly,

only one of the mutated residues interacted directly with the substrate; all others were

remote residues. Random mutagenesis experiments on the flavoenzyme vanillylalcohol

oxidase generated four single point mutants, each with enhanced reactivity for creosol

and other orthosubstituted 4methylphenols.16 In each mutant enzyme, the mutation

was located outside of the first shell. Finally, a mutant metalloβlactamase was

discovered through directed evolution that resulted in an enzyme with increased

hydrolytic efficiency toward cephalexin.17 This mutant contained four amino acid substitutions, two in the second coordination sphere of the metal ion and two far removed from the annotated active site.

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There are also a few examples where sitedirected mutagenesis studies have

shown that distal residues contribute to reactivity. In the metalloenzymes alkaline

phosphatase1821 and mandelate racemase,22 rational mutations to residues in the

second shell surrounding the metal ions have been reported previously, sometimes with

dramatic results. Studies showing participation in catalysis by multiple THEMATICS

predicted second and third shell residues have been reported recently by us for

Pseudomonas putida nitrile hydratase23 and human phosphoglucose isomerase,24 and

also for the Y family DNA polymerase from E. coli DinB.25 Further analysis of these and

additional enzymes are reported here, using the new POOL scores, new experimental

data, and compilations of experimental data from the literature.

Results

Optimizing POOL scores to predict distal residues

The top 8% of POOLranked residues typically have been taken to be the

predicted set of functionally important residues because this gives the best performance

against the CSA100,11 the benchmark set of annotated catalytic residues, for purposes

of predicting the known catalytic residues. The CSA100 is a 100enzyme subset of the

original, manually curated portion of the Catalytic Site Atlas;1 the 100 enzymes were

chosen to maximize sequence diversity with the goal of no detectable homology

between any two members of the subset. However, virtually all of the CSA100

annotated residues are firstshell residues and thus the cutoff that gives optimum

performance on the benchmark set is not necessarily the best cutoff for the prediction of

all of the residues that participate in catalysis, including the distal residues. For purposes

of prediction of both firstshell and more distant residues, we introduce the POOL

scores, which contain useful information and enable better predictions of functionally

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important residues, both inside and outside the first shell. Note that POOL scores are

used to rankorder the residues within a given protein structure, according to their

probability of participation in catalysis. However, the raw POOL scores are not

comparable between two different proteins, as they depend on protein size. It is

desirable to transform the POOL scores to a scale that is comparable across proteins.

Therefore the POOL scores within each protein are linearly transformed into Z scores.

Generally the few highestranked residues have Z scores that are many orders of

magnitude larger than those of most of the other residues. Therefore, the mean

and

standard deviation σP of all of the POOL scores within a protein are calculated a first

time and the residues with POOL scores greater than two standard deviations over the

mean are deemed outliers. The trimmed set of POOL scores, excluding the outlier

residues, is then used for the second calculation of the mean and standard deviation.

The POOL scores for all residues are then expressed as Z scores, as:

Zk = (Pk

t) / σPt , (1)

Here k is a residue index,

t represents the mean POOL score calculated on the

trimmed set and σPt represents the standard deviation for the trimmed set. Because the range of POOL scores is over many orders of magnitude in a given protein, the Z scores are rewritten as a logarithmic function logZP as:

logZPk = log10 (Zk + 1) (2)

Using the new POOL scores, we analyze enzymes across different enzyme classes.

Nitrile Hydratase

Nitrile hydratase (E.C. 4.2.1.84, NHase) from Pseudomonas putida utilizes lowspin,

noncorrinoid Co(III) to catalyze the hydrolysis of nitrile substrates to their corresponding

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amides. The reaction scheme is shown in Figure 1A. This type of lowspin Co(III) NHase

is prevalent as a biocatalyst for the industrial production of commodity chemicals such

as acrylamide on the kiloton scale, and also nicotinamide and 5cyanovaleramide.26

Catalysis by NHase affords a number of advantages over conventional catalysts,

including low energy consumption, less waste, high efficiency and product purity.

Pseudomonas putida NHase (ppNHase) is a heterodimeric metalloenzyme. The two

subunits, α and β, do not show mutual homology but both α and β do show a high

degree of homology to other known NHases.

Six firstshell residues in ppNH were reported previously2730 to be important for

catalysis: the cobaltcoordinating αC112, αC115, and αC117, the catalytic βR52 and

βR149, and the ligandbinding βY68. The two arginine residues are thought to

hydrogen bond to the cysteine residues which coordinate the metal ion. These arginine

residues therefore appear to stabilize the claw setting in the active site. We previously

reported23 first, second, and third shell residues predicted by THEMATICS7 to be

important for catalysis in ppNH (PDB ID: 3QXE) through sitedirected mutagenesis

(SDM) experiments. A total of eight residues were tested, five of which were predicted

by THEMATICS and three were not predicted; all eight residues are well conserved.

Mutations, made as conservatively as possible, at four of the five THEMATICSpredicted

residues showed significant loss of catalytic activity; one predicted residue, plus the

three residues not predicted, did not show significant difference from wild type upon

mutation. In the present work, we report additional experiments on distal residues, using

the POOL scores as a guide. The effects of the mutations are summarized in Table I. A

stereo view of the extended active site of ppNH is shown in Figure 1B. The cobalt ion is

rendered as a pink ball. The firstsphere residues are labeled in red font, the second

sphere in blue, and the third sphere in green.

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Figure 1C shows the POOL logZP scores as a function of POOL rank for ppNH.

The top 19 residues, corresponding to the top 5% of all residues in the dimer, have

positive logZP scores. For ppNH, ten out of the 15 top POOLranked residues were

previously tested by sitedirected mutagenesis, either reported in the prior literature or by

us, and all ten of them show a significant effect on catalysis. These ten include the six

firstshell residues reported previously (the cobaltcoordinating αC112, αC115, and α

C117, the catalytic βR52 and βR149, and the ligandbinding βY68).2730 Note that in

Fetype nitrile hydratase, the residue equivalent to βR149 of the Cotype nitrile hydratase analyzed here, βR141, has been reported30 to show no activity upon mutation

to Y or E, and significant decrease in activity upon mutation to K, although no specific

kinetics values were provided. The remaining four residues corresponding to significant

loss of activity upon mutation include three secondshell residues (αD164, βE56, and

βH147) and one thirdshell residue (βH71) reported by us to show a loss in catalytic

efficiency of at least 20fold.23 αD164 interacts with αC112 through a water molecule;

mutation to N retains the relative size, shape and hydrogen bonding capability while

removing the ability to form a negative charge. βE56 is within hydrogen bonding

distance to αC115, βR149 and βH147, while the secondshell residue βH147 is

located behind both catalytic residues βR52 and βR149. The thirdshell residue βH71

interacts through water molecules with the metal coordinating residue, αC115. Mutation

of βH71 to L removes hydrogen bond capabilities. In contrast, there are four variants

reported by us which exhibit an insignificant change in catalytic efficiency: secondshell

residues αE168 (involved in a salt bridge to βR52) and αR170 (Hbonded to αC117);

and thirdshell residues βY215 (Hbonded to the side chain of βR149 and to distal

residue βD172) and αY171 (Hbonded to distal residue βD210). These four residues

are all ranked lower by POOL (ranking 22nd, 32nd, 35th, and 40th, respectively), with negative logZP scores.

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Some additional residues with high POOL ranks, βY69, αK131, and βY63,

ranked fifth, sixth, and seventh, respectively, have now been studied by SDM. αK131 is

a secondshell residue located behind the firstshell residue βY68 with respect to the

substrate. βY69 is a thirdshell residue 11.9 Å from the Co ion and located behind α

K131 with respect to the substrate. βY63 is a secondshell residue behind the Co

coordinating αC115. Results of these mutations are summarized, together with prior

results, in Table I and illustrated in Figure 2. Figure 2 plots log10 of the ratio of the

catalytic efficiency for wildtype ppNH to that of the variant, as a function of the POOL

logZP score of the residue at the substituted position in the variant. The secondshell

variants αK131Q and βY63F both show an 11fold reduction in catalytic efficiency. The

thirdshell variant βY69F shows a small but significant loss in catalytic efficiency.

Notice in Figure 2 that the effect on catalytic efficiency generally declines with

declining POOL score and falls off to a kinetically small or insignificant effect for negative

values of the POOL logZP score. (A threefold or less decrease in catalytic efficiency is

not considered significant.) It is important to note in Table I that there are second and

third shell residues with positive POOL logZP scores that do show a significant effect on

catalytic efficiency. Thus the POOL logZP scores give some guidance about the number

of residues that participate significantly in catalysis; the residues with the higher, positive

scores tend to show the most participation in catalysis whereas residues with negative

scores tend not to show significant effects.

Phosphoglucose isomerase

Phosphoglucose Isomerase (PGI; E.C. 5.3.1.9) is an example of a moonlighting protein31

that has multiple functions. Inside the cell, PGI catalyzes the reversible isomerization of

glucose6phosphate to fructose6phosphate (Figure 3A), an essential step in

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glycolysis. Extracellular PGI has many roles including neuroleukin,32,33 autocrine motility

factor,34 and maturation factor.35 Human Phosphoglucose Isomerase (hPGI) is medically

important because certain mutations in the gene that encodes for hPGI have been

identified to cause nonspherocytic hemolytic anemia.36 In addition, hPGI is used as a biomarker because of its role as a tumorsecreted cytokine and angiogenic factor in certain types of cancer.37 The structure of hPGI is a dimer of two identical subunits.38

Figure 3B shows a stereo view of the extended active site of human PGI (hPGI)

and Figure 3C shows the POOL logZP scores as a function of POOL rank for hPGI. Like

ppNH, the POOL logZP scores for hPGI exhibit a sharp falloff after the first few

residues, but then an elongated tail, indicating a prediction of an active site with many

participating residues, including residues outside the first layer. The top 47 residues,

corresponding to the top 8%, have positive logZP scores.

Experiments confirmed the prediction of a spatially extended active site, as

shown in Table II. The catalytic residues for PGI were originally established by site

directed mutagenesis experiments39,40 on the Bacillus stearothermophilus enzyme.

Catalytically active residues for mammalian PGI were then identified by sequence

alignment and by xray structure determination.38,4143 Although the human and Bacillus

stearothermophilus enzymes share only 21% sequence identity, their active site

residues are well conserved. Kinetics data in Table II are for human PGI, except where

noted. The seven cases in parentheses (R273, E358, E217, K519, Q512, K211, and

K440) are for the homologous residues in the B. stearothermophilus enzyme (R207,

E290, E150, K425, Q418, K144, and K356, respectively) and all except for K440 are

presumed to be important also in human PGI. Figure 4 shows a plot of log10 of the ratio

of the catalytic efficiency for wildtype PGI to that of the variant, as a function of the

POOL logZP score of the residue at the substituted position in the variant.

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For hPGI, important firstshell residues, H389, R273, E358, E217, K519, Q512,

and K211, all rank among the top 45 residues and all have positive POOL logZP scores.

Second shell residues, E495, K362, and Q388, and third shell residues, H396 and H100,

that have been shown to be important for catalysis,24 are also among the highest ranking

residues. The secondshell residue D511, that has been shown24 to play a significant

role in catalysis, is ranked 57th and falls just below the range of residues with positive

scores. There are three highly ranked second and third shell residues, Y341, Y274,

and N386 that proved to be false positives, at least with respect to singlesite mutation.

Residues that are highly conserved but ranked well below those with positive scores,

N154, S185, and K440, are true negatives and the effects of mutation on catalysis are

not significant.

Ketosteroid isomerase

∆53 Keto steroid isomerase (KSI; EC 5.3.3.1) is a wellstudied4451 enzyme with high

catalytic activity, with a rate approaching the diffusioncontrolled limit. KSI catalyzes the

isomerization of a ∆53ketosteroid to a ∆43ketosteroid (Figure 5A), involving CH bond

cleavage and formation through a dienolate intermediate. KSI has a metabolic role in the

degradation of steroids in bacterial species that can live on steroids as their sole carbon

source. Highresolution crystal structures of KSI from Pseudomonas putida (ppKSI, PDB

ID: 1OPY52) and Commamonas testosteroni (PDB ID: 1QJG53) reveal that, although

these two enzymes share only 34% sequence identity, their active site residues are

conserved and structurally superimposable. Figure 5B shows a stereo view of the active

site of ppKSI.

While ppKSI and hPGI both catalyze isomerization reactions and are both

members of EC class 5.3, these two isomerases possess very different types of active

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sites.24 In the plot of POOL logZP score as a function of POOL rank for the residues of

ppKSI, shown in Figure 5C, the residues of ppKSI exhibit a sharp falloff after the first

few residues and no extended tail, corresponding to a prediction of a compact active

site. The 13 highest scoring residues, comprising 10% of this small protein, have positive

logZP scores. The top three residues in the POOL ranking, Y32, Y57, and Y16, form an

important hydrogen bonding network in the active site of KSI;50 Y16 stabilizes the

dienolate intermediate and serves as a proton donor. The Y16F variant shows a 550fold

54 55 reduction in kcat/KM relative to wild type; the Y16S variant shows an 18fold reduction.

While the Y32F and Y57F variants do not show major differences from wild type, with

54 1.3 and 2.9 fold reductions in kcat/KM, respectively, kcat/KM for the Y57S variant is 66 fold less55 than wild type (see Table III). Table III and Figure 6 show that mostly first

shell residues participate in catalysis; residues outside the first shell have only small

effects, as predicted.

Alkaline Phosphatase

Alkaline phosphatase (AP, EC 3.1.3.1) has been widely studied using both directed

evolution and rational protein design approaches.21 AP is a dimeric metalloenzyme containing two zinc ions and one magnesium ion per subunit and it catalyzes the reversible hydrolysis of phosphomonoesters to yield inorganic phosphate plus an alcohol; the reaction mechanism is shown in Figure 7A. In the crystal structure of E. coli

AP (PDB ID: 1ALK56), there is an inorganic phosphate ion bound to the two zinc ions

19 (Zn1 and Zn2) and to the guanidinium group of R166. The active site region of the protein includes D101, S102, A103, the three metal ions and their coordinating residues, and R166;56 R166 has been shown to be important for transition state stabilization and for discrimination between phosphates and sulfates.57,58 There is a hydrogen bond

network that includes hydrogen bonds between D101 and R166 and between R166 and

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a water molecule.59 K328 interacts with the phosphate group in the active center through

a water mediated hydrogen bond. A stereo image of the active site is shown in Figure

7B.

Two interesting mutations, designed specifically to increase the catalytic activity

of AP, are associated with the firstshell residue D153 and the secondshell residue

D330. D153 is involved in an ion pair interaction with K328 and in a watermediated

interaction with the Mg2+ ion.21 D153 also serves to position the catalytic residue, R166.

Using rational protein design methods, four different singlepoint mutations were made

at the D153 position in an attempt to understand more clearly its role and to increase the

catalytic efficiency of the protein.6062 Three of the four mutations, D153G, D153E, and

D153A, resulted in an increased catalytic rate.

In an effort to increase the turnover rate to a level comparable to that of

mammalian enzymes, while allowing the protein to retain its high thermostability, Muller

and coworkers21 assumed that while mutations to residues in the active site most often

had a negative effect on catalysis, residues outside the catalytic site may also influence

catalysis. Using directed evolution approaches, they showed that variants with double or

triple mutations of D153, K328, and D330 showed increased activity over wild type while

still maintaining thermostability.21

Figure 7C shows the POOL logZP scores as a function of POOL rank for E. coli

AP. The top 36 residues, or 8% of all residues, have positive logZP scores; these top 36

include the two catalytic residues S102 and R166, D101 in the active site, and the eight

Zn and Mg coordinating residues D51, T155, E322, D327, H331, D369, H370, and

H412. Note that the metalcoordinating residues H370 and E322 are ranked third and

fifth, respectively, by POOL (kinetics data not available). Also included is the second

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shell residue H372, which hydrogen bonds to the Zncoordinating residue D327.

Mutation of H372 to alanine shows no change in Zn binding affinity, but kcat of the H372A variant is ninefold less than that of wild type, with a 3.7fold increase in catalytic

18 efficiency (kcat/KM).

In this work, two additional secondshell residues in the top 36, H86 and M53, the thirdshell residue E57 at rank 17, and the lowerranked secondshell residues Q435,

E150, and S105, were studied by sitedirected mutagenesis. Additional variants were also made for H372 and D330, two secondshell residues previously shown to influence activity. Table IV shows the POOL rank, POOL logZP score, and change in catalytic efficiency for some E. coli AP variants. In this case, the logZP=0 cutoff for POOL scores results in overprediction of the essential residues for catalysis. While all of the residues known to have significant, singlehanded effects on activity are included in the top 20 predicted by POOL, predicted residues H86, E57, and M53 proved to be false positives with respect to singlepoint mutations.

Other examples of the importance of distal residues

Mandelate racemase (EC 5.1.2.2) catalyzes the interconversion of the (R) and (S) enantiomers of mandelic acid (Scheme 1) via abstraction of a proton from the αcarbon atom (6365).

Scheme 1

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It is a divalent cationdependent protein and in the Pseudomonas putida crystal structure

(PDB ID: 2MNR), the Mn2+ ion is coordinated by D195, E221, E222 and E247.66 The

reaction proceeds via a twobase mechanism; H297 acts as the (R)- specific acid/base

catalyst64 while K166 acts as the (S)- specific acid/base catalyst.65 The secondshell

residue D270 forms a hydrogen bond with the catalytic H297. The single mutation

D270N results in a 10,000fold decrease in enzyme activity compared to wild type for

both (R)- and (S) mandelate substrates.22 The N270 side chain in the structure of the

variant is superimposable on the D270 side chain in the structure of the wild type, and

the remainder of the two structures are identical except that the side chain of the

catalytic H297 is “rotated and displaced toward the binding site” in the mutant

22 structure. It was argued that D270 is necessary to impart the correct pKa to the

catalytic H297.22 The two catalytic bases H297 and K166 and the important secondshell

residues D270 are all highly ranked by POOL, with logZP scores of 0.71, 0.65, and 0.65,

respectively.

Carbonic anhydrase isoform II (CAII, EC 4.2.1.1) is a zincdependent metalloenzyme

that catalyzes the reversible hydration of carbon dioxide:67

Scheme 2

The hydrolysis of carbon dioxide to the bicarbonate ion and a proton occurs via a two

step mechanism. In the first step, a zincbound hydroxide ion acts as the nucleophile

which attacks CO2 to form a zincbound bicarbonate intermediate. This intermediate is

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then displaced by a water molecule creating a zincH2O complex and free bicarbonate ion. In the rate determining step, the zincbound hydroxide is regenerated through the transfer of a proton to the solvent facilitated by the active site histidine residue, H64, which acts as a proton shuttle.68,69 In the crystal structure of CAII, (PDB ID: 1CA270) the zinc ion is tetrahedrally coordinated with the side chains of H94, H96 and H119 and a hydroxide ion. T199 accepts a hydrogen bond from the zincbound hydroxide ion and donates a hydrogen bond to the side chain of E106. T199 also helps to orient the

71 hydroxide ion properly for nucleophilic attack on the substrate, CO2. The secondshell residue H107 when mutated to Y causes CAII deficiency syndrome in vivo.72 For another secondshell residue E106, lossofcharge variants E106Q and E106A show decreased catalytic rate constants by factors of 850 and 110, respectively; the variant E106D that maintains the negative charge shows no change in catalytic rate from that of wild type.73

For CAII, only THEMATICS and ConCavity data were used in the POOL analysis because of residue numbering disparities in the INTREPID data. The top 19 residues have positive logZP scores. The Zncoordinating histidine residues H94, H119, and H96 are the top three ranking residues in POOL. The important secondshell residue E106 ranks fourth with a logZP score of 1.9. The proton shuttle H64 ranks sixth with a logZP score of 0.91. H107 in the second shell, mutation of which is associated with disease, ranks seventh with a logZP score of 0.58. The hydroxide activator T199 ranks tenth with a logZP score of 0.15.

Discussion

Distal residues can be important contributors to enzyme catalysis but their participation is hard to predict computationally by prior methods. Distal residues are clearly important in computationally driven enzyme design, but better understanding of how to use them is

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needed.74 While there are presently few enzymes with extensive data on variants with

substitutions in distal positions, the examples presented here suggest that the logZP

POOL scores can predict the distal residues and provide useful guidance about the

extent of distal residue participation.

The logZP scores provide a more accurate prediction of distal residue

participation than the previouslyutilized 810% cutoff from the top of the POOL rank

order. For most instances, the present logZP score cutoff (logZP > 0) generates fewer

false positives than the 810% cutoff. More importantly, the logZP method allows that

some proteins have much more extensive distal residue participation than others.

The multilayer active sites of Pseudomonas putida nitrile hydratase and of

human phosphoglucose isomerase are predicted by the logZP scores, as is the single

layer active site of Pseudomonas putida ketosteroid isomerase. The logZP score cutoff

utilized here results in overprediction of distal residue involvement in E. coli alkaline

phosphatase. This may be because of extensive collective interactions in AP, such that

mutation at a single position may have no significant effect on catalysis because a

sufficient number of additional important residues remain. We note that some of the

positions predicted by POOL, such as D153 and D330, for which singlepoint variants

show little difference from wild type, have been shown to be significant in two and three

point variants.21 While fewer experimental data points are available for Pseudomonas

putida mandelate racemase and for human carbonic anhydrase II, the POOL logZP

scores properly predict the previously reported participation of distal residues.

For ketosteroid isomerase, the two residues contributing the most to catalysis,

D40 and Y16, are both ranked in the top four by POOL. The 66fold loss in catalytic

efficiency observed55 for the Y57S variant suggests that the aromatic ring of this residue,

19 John Wiley & Sons

ranked second by POOL, is important for catalysis. From very recent xray solution scattering and NMR studies of the Y57S variant it was concluded that, while the overall size of the variant structure is reduced relative to wild type, the active site cavity is enlarged,75 suggesting that the bulky phenyl group is necessary to maintain the correct spatial arrangement within the active site. The number 1 POOL ranking for Y32 is an apparent false positive. It is possible that the very intense electric field76 inside the active site is not significantly diminished by the loss of one residue in the second shell. Another possible explanation is that, upon mutation of Tyr to Phe, a water molecule takes the place of the phenolic hydroxyl group and assumes its role, perhaps then allowing catalytic efficiency to be maintained.

The logZP scores provide richer information about the importance of amino acid residues in the function of the enzyme than do other computational predictors, including the simple POOL ranks used previously. The cutoff utilized in the present work corresponds to the best performance for the admittedly small available set of proteins with experimental mutagenesis data on distal residues. More examples with extensive experimental data on distal residue mutagenesis are needed to establish the optimum cutoff for the logZP scores.

Distal residues influence the polarity, proton transfer properties, electrostatic ambience, spatial arrangement, and flexibility of active site residues. While the present method predicts most of the distal residues that influence catalysis, it is unable to predict the effects of some substitutions that alter the orientation or relative positions of the catalytic residues by virtue of their steric bulk, for instance in the M105A variant of ketosteroid isomerase.24

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Since distal residues can play key supporting roles in catalysis, and since the

electrostatic properties of the residues in and around the active site are critically

important, these factors need to be considered in rational protein design.

Materials and Methods

Computational methods

The protein structures used as the input data for all calculations were downloaded from

the Protein Data Bank (PDB, http://www.rcsb.org/pdb/).77 Coordinates for all the proteins

in the test set were analyzed by Theoretical Microscopic Titration Curves

(THEMATICS)5,78 using the method of Wei.7 POOL calculations3 were performed as

described previously.4 Unless otherwise noted, input features include THEMATICS

metrics, INTREPID evolutionary scores79 and ConCavity10 surface geometry features.

INTREPID scores were obtained using the Berkeley phylogenomics web server.80 The

structureonly version of ConCavity was used.

The Ligand Protein Contacts – Contacts of Structural Units (LPCCSU) server was used

to identify the ligand and/or metal binding residues and the residueresidue

contacts,81,82 in order to assign residues to shells. Both the known catalytic and

ligand/metal binding residues were considered firstshell for this study.

Experimental mutagenesis data reported previously were obtained from individual

literature references, with the help of the BRENDA enzyme database83 and from the

Protein Mutant Database (http://www.genome.ad.jp/dbgetbin/www_bfind?pmd) within

the DBGET database retrieval system (http://www.genome.jp/dbget/).

Nitrile Hydratase

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Expression, purification, and kinetics analysis were performed exactly as described

previously.23

Alkaline Phosphatase

Site-Directed Mutagenesis

An expression plasmid pEK29 84 generously provided by E.R. Kantrowitz (Boston

College), encoding the E. coli alkaline phosphatase gene, was used for protein expression and mutagenesis. Mutations were constructed using a Quikchange site directed mutagenesis kit (Agilent Technologies, Santa Clara, CA). The mutated genes were sequenced to verify the construct (Massachusetts General Hospital DNA core,

Cambridge, MA). After confirmation of the intended mutation, the plasmid was transformed into SM547 (a gift from E.R. Kantrowitz)84 competent cells and selected on

LB agar containing 100 g/mL ampicillin.

Protein Expression and Purification

Cells were grown at 37°C in 1 L of 2x YT media containing ampicillin (100 g/mL) for 12

hours. The cells were harvested, washed, and osmotically shocked as previously

described85 and then protein was precipitated, suspended, dialyzed and purified on a

HiTrap FastFlow Q column (GE Healthcare) as previously described.84 Protein fractions

greater than 95% pure as judged by SDSPAGE and Coomassie blue staining were

pooled and stored at 20°C. The concentration of all proteins was determined by

Bradford assay (BioRad, Hercules, CA) using bovine serum albumin as a standard.

Kinetics

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Alkaline phosphatase activity was measured spectrophotometrically utilizing p

nitrophenyl phosphate as the substrate. Formation of pnitrophenolate was monitored at

410 nm at room temperature in Tris buffer (1.0 M TrisHCl pH 8.0). Initial velocities were

calculated utilizing a molar absorptivity coefficient of 1.42 x 104 M1cm1.84 Nonlinear

regression was performed to calculate KM and kcat values using GraphPad Prism 5

version 5.02.

Acknowledgments

The support of National Science Foundation grant MCB1158176 is gratefully

acknowledged. We also acknowledge the students in the Principles of Chemical Biology

laboratory section at Northeastern University and Michelle Silva, Teaching Assistant, for

construction of some of the AP variants.

Disclosure: MJO currently has a research grant from Mathworks, Inc. in support of

another project.

23 John Wiley & Sons

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Table I. Residue POOL rank, POOL logZP score, and loss of catalytic efficiency for ppNH variants. Note that the residue ranked fourth, βR149, has been reported to be important for catalysis, but numerical kinetics data have not been reported.

POOL POOL logZP (kcat/KM) wild type Variant Shell rank score / (kcat/KM) mutant Reference αC115A First 1 2.0 >1.0 x 105 (27) βY68F First 2 1.8 3.8 x 102 (28) αC112A First 3 1.3 >1.0 x 105 (27) βR149Y First 4 1.0 see text (30) see text βY69F Third 5 0.99 6 this work αK131Q Second 6 0.94 11 this work βY63F Second 7 0.94 11 this work βE56Q Second 8 0.89 2.3 x 102 (23) βH147N Second 9 0.85 1.1 x 102 (23) αC117A First 10 0.79 >1.0 x 105 (27) αD164N Second 11 0.56 20 (23) βR52K First 12 0.52 1.3 x 103 (29) βH71L Third 15 0.37 25 (23) αY118F Second 17 0.047 8 this work αE168Q Second 22 0.029 3.7 (23) βY215F Third 32 0.054 3.3 (23) αR170N Second 35 0.062 1.6 (23) αY171F Third 40 0.067 2.1 (23) αR195Q Third 51 0.072 3 this work

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Table II. Residue POOL rankings, POOL logZP score, and loss of catalytic efficiency for PGI variants. Parentheses indicate kinetics data reported for the homologous residue in the B. stearothermophilus enzyme (with hPGI numbering). All other kinetics data are for human PGI. POOL POOL (k /K ) Variant Shell logZP cat M wild type Reference rank / (k /K ) score cat M mutant H389L First 1 2.0 >10000 (24) H396L Third 3 1.3 24 (24) (R273A) First 6 0.79 (170000) (39) Y341F Third 11 0.66 1.5 (24) (E358Q) First 13 0.59 (2100) (40) E495Q Second 14 0.58 250 (24) (E217Q) First 20 0.49 (130000) (40) H100L Third 21 0.48 630 (24) Y274F Second 23 0.34 2.2 (24) N386A Second 25 0.22 2.8 (24) K362A Second 26 0.27 >10000 (24) Q388A Second 29 0.18 19 (24) (K519A) First 39 0.06 (390) (39) (Q512A) First 44 0.02 (120) (40) (K211A) First 45 0.01 (19) (39) D511N Second 57 0.03 230 (24) N154Q Second 135 0.08 3.8 (24) S185A Second 140 0.08 3.5 (24) (K440A) Third 162 0.08 (1.0) (39)

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Table III. Residue POOL rankings, POOL logZP score, and change in catalytic efficiency for Ps. putida KSI variants. POOL POOL (k /K ) / Variant Shell logZP cat M wild type Reference rank (k /K ) score cat M mutant Y32F Second 1 1.9 1.3 (54) Y32S “ “ “ 3.6 (55) Y57F First 2 1.4 2.9 (54) Y57S “ “ “ 66 (55) Y16F First 3 1.4 550 (44) Y16S “ “ “ 18 (55) D40N First 4 1.1 334000 (86) W120F First 5 0.20 13 (87) F56L First 6 0.13 3.6 (87) D103N First 9 0.074 27 (51) E39Q Second 12 0.015 2.4 (24) F86L First 14 0.006 9.2 (87) M105A Third 16 0.026 7.6 (24) M84A Second 23 0.05 0.98 (24) M31A Second 34 0.05 2.1 (24) C97S Second 39 0.05 1.3 (88) C81S Second 48 0.05 0.98 (88) C69S Second 58 0.05 0.92 (88)

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Table IV. Residue POOL rankings, POOL logZP score, and change in catalytic efficiency for E. coli alkaline phosphatase variants. (Residue numbering follows the PDB file 1ALK.) POOL Pool (k /K ) / Variant Shell logZP cat M wild type Reference Rank (k /K ) score cat M mutant D51N First 1 2.8 12 (89) D369N First 2 2.6 95 (19) D327N First 4 2.5 100 (90) D327A First 4 “ >1,000,000 (90) H412N First 6 2.0 130 (91) H331E First 7 1.2 972 (62) D101S First 8 1.0 0.2 (60) H372A Second 9 1.0 0.27 (18) H372D Second 9 “ 3.3 This Work H372L Second 9 “ 2.5 This Work D153G First 10 0.72 0.2 (60) D153N First 10 “ 1.1 (61) R166A First 11 0.60 313 (84) K328A First 13 0.47 3.8 (92) H86L Second 14 0.45 3.2 This Work E57Q Third 17 0.17 1.8 This Work T155M First 18 0.16 678 (19) S102A First 19 0.16 150,000 (93) M53A Second 21 0.13 1.5 This Work M53T Second 21 “ 2.4 This Work D330N Second 22 0.06 0.2 (21) D330N Second 22 “ 2.1 This Work Q435E Second 44 0.03 1.7 This Work T100V Second 51 0.03 0.3 (20) V99A Second 100 0.06 0.2 (20) E150Q Second 106 0.06 3.7 This Work S105A Second 136 0.06 2.1 This Work

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Figure 1. For Pseudomonas putida Nitrile hydratase: A) Reaction scheme; B) Stereo view of the extended active site. The Co ion is rendered as a pink ball; font color indicates location – Red, first sphere – Blue, second sphere – Green, third sphere; C) POOL logZP score as a function of POOL rank for the top 25 POOL- ranked residues. 246x386mm (300 x 300 DPI)

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Figure 2. log10 of the ratio of the catalytic efficiency of WT over variant as a function of the POOL logZP score of the substituted position in the variant for ppNH. 99x60mm (120 x 120 DPI)

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Figure 3. For human Phosphoglucose isomerase: A) Reaction scheme; B) Stereo view of the extended active site - Font color indicates location – Red, first sphere – Blue, second sphere – Green, third sphere; C) POOL logZP score as a function of POOL rank for the 50 top-ranked residues. 139x192mm (300 x 300 DPI)

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Figure 4. log10 of the ratio of the catalytic efficiency of WT over variant as a function of the POOL logZP score of the substituted position in the variant for human phosphoglucose isomerase. 101x83mm (120 x 120 DPI)

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Figure 5. For Pseudomonas putida Ketosteroid isomerase: A) Reaction scheme; B) Stereo view of the extended active site – Font color indicates location – Red, first sphere – Blue, second sphere – Green, third sphere; C) POOL logZP score as a function of POOL rank for the top 20 POOL-ranked residues. 131x156mm (300 x 300 DPI)

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Figure 6. log10 of the ratio of the catalytic efficiency of WT over variant as a function of the POOL logZP score of the substituted position in the variant for Ps. putida ketosteroid isomerase. 212x176mm (120 x 120 DPI)

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Figure 7. For E. coli alkaline phosphatase: A) Reaction scheme; B) Stereo view of the active site. The Zn ions are rendered as grey balls; – Font color indicates location – Red, first sphere – Blue, second sphere – Green, third sphere; C) POOL logZP score as a function of POOL rank for the top 50 POOL-ranked residues. 241x359mm (300 x 300 DPI)

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Cover image: Stereo view of the extended active site of Pseudomonas putida Nitrile hydratase, as predicted by the Partial Order Optimum Likelihood (POOL) logZP scores. The Co ion is in pink, the first sphere residues in red, second sphere in blue, and third sphere in green. 149x148mm (300 x 300 DPI)

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